Prepare for and practice interview questions from Pivotal Software, Inc..

Pivotal Software, Inc. Interview Questions

pivotal transforms how the world builds software. pivotal combines the silicon valley state of mind, modern approach, and infrastructure with organizations’ core expertise and values. we enable the leading companies in the world to innovate by employing an approach focused on building software. our methodology is about evolving, in both development and innovation, and our culture is empowering. our team uses agile and lean approaches to teach next-generation developers to create and build new solutions. we optimize for change so enterprises can move at start-up speeds and with greater business agility.

pivotal transforms how the world builds software. pivotal combines the silicon valley state of mind, modern approach, and infrastructure with organizations’ core expertise and values. we enable the leading companies in the world to innovate by employing an approach focused on building software. our methodology is about evolving, in both development and innovation, and our culture is empowering. our team uses agile and lean approaches to teach next-generation developers to create and build new solutions. we optimize for change so enterprises can move at start-up speeds and with greater business agility.

Overview

Pivotal Software, Inc. Interview Guides

Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

Random SQL Sample

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

Pivotal Software, Inc. Salaries by Position

<h3>Job Description</h3><div>Job Description<div>Salary: $200,000-$300,000 + DOE + 20% bonus Pivotal Life Sciences Location: San Francisco, CA About Us: Pivotal Life Sciences (PLS), part of Nan Fung Group, is a global investment platform focused on life sciences. Leveraging our strong capital base and long-term commitment, we partner with scientists, entrepreneurs, corporations, and investors to advance the life science industry. Our AI team is building the best-in-class data intelligence platform supporting all steps of the venture capital investment process, from deal sourcing to diligence and portfolio value creation. Ultimately, PLS strives to be a scientifically and data driven investor across the life science startup ecosystem. Learn more at www.pivotallifesciences.com The Role: ML Engineer We are seeking an experienced ML / software engineer with expertise in Machine Learning, MLOps, and Generative AI to join our Data Intelligence team. In this role, you will work alongside data science, data infrastructure, computational biology, and venture investment teams to build and maintain state-of-the-art ML models, generative AI systems, and MLOps pipelines build a best-in-class AI system for investment decision-making in the biotech venture capital space. These AI systems function across all aspects of the biotech venture lifecycle, such as company sourcing, due diligence, portfolio value creation, disease mapping, clinical trial success prediction, and more. This is a great opportunity to work on a range of high impact, high visibility AI projects in a growing team, with exposure to the best life science companies today. Responsibilities: ML/AI Operations: - Create environments for building, testing, and deploying AI applications, including natural language search and generative AI / LLM models. - Work closely with scientists and engineers to integrate AI and ML models into production systems. - Benchmark, evaluate, and document model performance, providing recommendations for continuous improvement. - Work with data engineering and data science teams to ensure extraction, transformation, and delivery of data from diverse data sources. - Use structured and unstructured data in data lake and warehouse to extract investment signal from noise. - Maintain internal frameworks and libraries to work with public and proprietary AI models and technologies. Cloud AI Systems: - Leverage AWS infrastructure to ensure efficient, scalable, reliable, and maintainable delivery of AI models. - Architect ML/AI applications at various scales. - Participate in extending our ML/AI systems across the US and China. Technical Leadership and Collaboration: - Collaborate with data science to determine user requirements for new ML/AI systems. - Lead technical and engineering design for ML/AI systems - Lead design reviews for ML/AI applications - Act as internal technical expert to assist internal teams in utilizing AI systems and technologies - Contribute to setting long-term technical direction, roadmaps, and standards for ML/AI that align with existing and future systems and processes. Qualifications: - Bachelor's degree in Computer Science, Machine Learning, AI, or a related field; Master's or PhD preferred. - 5+ years of relevant experience in machine learning and AI, ideally in an ML engineering or MLOps role. - Strong proficiency in Python. - Deep understanding of machine learning algorithms and principles, with the ability to implement them in production environments. - Experience with recent large language models (e.g., GPT-4o, LLama3, Claude) and adjusting LLM model weights through fine-tuning. - Experience working with vector databases such as pgvector, ChromaDB, etc. - Experience with AI platforms such as SageMaker, AWS Foundational Models, Hugging Face, etc. - Proven experience architecting cloud infrastructures on Amazon Web Services (AWS). - Familiarity with ML workflows and pipelines, and experience with orchestration systems such as Airflow, Metaflow, Prefect, or similar. - Proficiency in building machine/deep learning models using frameworks like PyTorch, TensorFlow, Keras, or Scikit-learn. - Knowledge of relational database architecture and data management; SQL expertise preferred. - Familiarity with software development practices such as unit testing, code reviews, and version control. - Excellent analytical and communication skills. - Proficiency in English. Additional Requirements: - Ability to work independently and collaboratively in a fast-paced environment. - Must have US work authorization; we are unable to sponsor visas at this time. - Hybrid work schedule: Able to be in the San Francisco office at least 3 days per week (Monday, Wednesday, Thursday), with the option to work from home 2 days per week. Compensation: - Salary Range: $200,000 - $320,000 total compensation package - Bonus: Up to 20% annual target performance bonus --- Join us in building innovative solutions that drive smart investments in the life sciences sector. If you are a proactive ML/AI Engineer with a passion for integrating cutting-edge AI models into production systems, we would love to hear from you.<ul></ul> </div></div>

Pivotal Software, Inc. Interview Questions

Overview

Pivotal Software, Inc. Interview Guides

Pivotal Software, Inc. Interview Questions

Pivotal Software, Inc. Salaries by Position

Pivotal Software, Inc. Opening Jobs